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Digital exposure notifications (DEN) systems were an emergency response to the coronavirus disease 2019 (COVID-19) pandemic, harnessing smartphone-based technology to enhance conventional pandemic response strategies such as contact tracing. We identify and describe performance measurement constructs relevant to the implementation of DEN tools: (1) reach (number of users enrolled in the intervention); (2) engagement (utilization of the intervention); and (3) effectiveness in preventing transmissions of COVID-19 (impact of the intervention) [...]

To assess the impact of patient health literacy, numeracy, and graph literacy on perceptions of hypertension control using different forms of data visualization.

As the informatics community grows in its ability to address health disparities, there is an opportunity to expand our impact by focusing on the disability community as a health disparity population. Although informaticians have primarily catered design efforts to one disability at a time, digital health technologies can be enhanced by approaching disability from a more holistic framework, simultaneously accounting for multiple forms of disability and the ways disability intersects [...]

Plain language in medicine has long been advocated as a way to improve patient understanding and engagement. As the field of Natural Language Processing has progressed, increasingly sophisticated methods have been explored for the automatic simplification of existing biomedical text for consumers. We survey the literature in this area with the goals of characterizing approaches and applications, summarizing existing resources, and identifying remaining challenges.

To assess the efficacy of interruptive electronic alerts in improving adherence to the American Board of Internal Medicine's Choosing Wisely recommendations to reduce unnecessary laboratory testing.

Chest pain is common, and current risk-stratification methods, requiring 12-lead electrocardiograms (ECGs) and serial biomarker assays, are static and restricted to highly resourced settings. Our objective was to predict myocardial injury using continuous single-lead ECG waveforms similar to those obtained from wearable devices and to evaluate the potential of transfer learning from labeled 12-lead ECGs to improve these predictions.

To develop a usability checklist for public health dashboards.

To identify common medication route-related causes of clinical decision support (CDS) malfunctions and best practices for avoiding them.

To determine the extent of implementation, completeness, and accuracy of Structured and Codified SIG (S&C SIG) directions on electronic prescriptions (e-prescriptions).

Abnormalities in impulse propagation and cardiac repolarization are frequent in hypertrophic cardiomyopathy (HCM), leading to abnormalities in 12-lead electrocardiograms (ECGs). Computational ECG analysis can identify electrophysiological and structural remodeling and predict arrhythmias. This requires accurate ECG segmentation. It is unknown whether current segmentation methods developed using datasets containing annotations for mostly normal heartbeats perform well in HCM. Here, we present a segmentation method to effectively identify ECG waves across 12-lead [...]